Search Results (34)

Urban regeneration increasingly depends on the governance mechanism that makes design-intensive change administratively possible. This paper examines a semi-formal coordination forum established in Hsinchu, Taiwan, during the mayoralty of Chih-Chien Lin (2014–2022). Utilizing elite interviews and documentary sources, the research reconstructs how the forum convened bureau heads, external consultants, designers, and other stakeholders to coordinate a portfolio of regeneration projects. The findings indicate that the forum functioned as a cross-boundary governance interface. Rather than replacing formal procedures, it operated upstream and in parallel to clarify responsibilities, mediate design judgment, enhance procurement credibility, and expedite implementation through iterative review. Furthermore, the analysis demonstrates that the forum cannot be classified within established governance design categories such as steering committee, task force, project office, or design review panel. Instead, it represents a hybrid model that integrates diverse characteristics, with its value derived from a complex micro-organization of actors and routines over time. Full article

As high-density cities face severe conflicts between urban expansion and limited ecological space, exploring the potential drivers of carbon sequestration within urban green spaces is crucial. The overarching aim of this study is to establish an interpretable, model-based analytical framework for assessing the Annual Carbon Fixation Rate (ACFR). To address the limitations of linear models and “black-box” machine learning algorithms, this study analyzed 149 urban parks in Nanjing by coupling Sentinel-2 high-resolution data with a Random Forest algorithm and the SHAP framework to model Annual Carbon Fixation Rate. The model achieved high predictive reliability (R² = 0.9690). This study quantitatively identified critical nonlinear thresholds: an impervious surface proportion exceeding 30% is associated with a structural decline in carbon sinks, while the optimal Leaf Area Index interval for maximum efficiency is 2.5–3.5. Moreover, the present research identified a potential model-derived ecological compensation effect; optimizing vegetation community structures under high anthropogenic disturbance showed a 23.9% higher modeled marginal ACFR response compared to low-disturbance habitats. This explainable framework attempts to translate complex model-derived biophysical associations into referenced quantitative thresholds. Importantly, the ACFR and derived thresholds represent remote sensing-based model estimates rather than field-measured ecological causality, serving as exploratory planning references. These findings challenge the assumption that greening is inefficient in degraded environments and provide concrete control indicators for targeted micro-renewal and sustainable urban regeneration. Full article

As global urban development shifts towards stock upgrading and cultural tourism consumption, historic and cultural districts have become crucial spatial carriers for reshaping local identity and driving urban regeneration. Although the literature explores cultural value, current research remains limited to macro-scale assessments, leaving a gap in micro-scale, quantitative identification of spatial narrative capacity. To address this, the concept of ontological narrative is introduced, and a three-dimensional framework integrating physical space, functional formats, and historical events is constructed. Using event space as the unit of measurement, a mixed-methods approach combining spatial syntax, kernel density estimation, and the Analytic Hierarchy Process is applied to Chaozong Street in Changsha. The findings indicate that narrative intensity exhibits a spatial pattern of main-axis agglomeration and deep-alley attenuation. High-value nodes concentrate along primary streets with high accessibility. Conversely, narrative efficacy declines in branch alleys and functionally deficient zones. Furthermore, a four-quadrant diagnosis reveals widespread structural decoupling, such as high historical value paired with low vitality. This shows that historical assets require functional activation to become effective narratives. This research provides a precise analytical tool, grounded in node diagnosis, to counter homogenized urban renewal by fostering differentiated cultural expression. Full article

As a form of living heritage, Historic Urban Landscapes (HULs) have long been limited by the static perspectives and reductionist tendencies of conventional conservation and research approaches. Although the geological and archaeological concept of “stratification” offers a methodological basis for understanding the diachronic evolution of heritage, its unidimensional temporal lens fails to capture the inherent complexity and systemic nature of historic urban landscapes. To address this gap, this study proposes a “multidimensional stratification” theoretical framework through theoretical critique and paradigm reconstruction. The framework introduces innovations at the ontological, epistemological, and methodological levels, positing that the evolution of historic urban landscapes emerges from the nonlinear interaction and dynamic interweaving of four core dimensions: time, space, society, and value. It further systematizes five intrinsic attributes of such landscapes: authenticity, integrity, continuity, adaptability, and dynamism. Building on this foundation, the paper constructs a systematic analytical pathway—elements–processes–patterns–modes–drivers–characteristics—that enables dynamic analysis from micro-level identification to macro-level generalization, offering a scalable tool for HUL conservation and regeneration. To demonstrate the framework’s applicability, the historic urban area of Shenyang—a nationally designated historical and cultural city—is selected as a case study. Its urban landscape comprises four core districts: the Shengjing City District, the South Manchuria Railway Concession District, the Commercial Port District, and the Tiexi Industrial District, representing historical strata from the Qing dynasty capital, modern colonial planning, commercial opening, to industrial heritage. Using the multidimensional stratification approach, this study elucidates the spatial complexity, temporal nonlinearity, social dynamism, and value pluralism embedded in Shenyang’s historic urban area. Corresponding conservation strategies grounded in holism, dynamism, and differentiation are proposed. The research not only advances the theoretical understanding of HUL but also provides a novel paradigm—integrating holistic, dynamic, and operational perspectives—for the conservation, renewal, and regenerative practice of historic urban landscapes worldwide. Full article

Precise assessment of commercial service facilities (CSFs) is a vital pillar for megacity governance. However, existing evaluations rely on static population and 2D metrics, overlooking behavioral heterogeneity and 3D spatial supply at the micro scale. This study constructs a “3D Supply–Group Demand–Matching” framework at the community level. On the supply side, a Building Coupling Entropy (BCE) model integrates 3D volume and morphology to characterize service capacity. On the demand side, a dynamic behavioral model measures multi-group needs. Mismatch patterns are identified using the Entropy-modified Spatial Disparity Ratio (ESDR). Using Guangzhou as a case, the results reveal three paradigms: (1) Core districts exhibit rigid path dependency, where first-tier sub-districts rose from 48 to 51, and elderly service shortages in old areas plummeted by nearly 80% via micro-regeneration; (2) Growth poles show spatial fragmentation, with core labor demand spilling over but infrastructure lagging, creating a fast production–slow urbanism mismatch; (3) Far-suburban areas reduced extreme-shortage sub-districts from 38 to 34, identifying resource islands besieged by residential demand. Overall, the framework elucidates the shape–flow mismatch mechanism and provides a transferable basis for precision zonation governance, supporting a shift from static quantity-based allocation to dynamic quality-oriented provision in high-density megacities. Full article

In the digital economy era, Urban vitality has transitioned into an intertwined Virtual-Physical system. This study examines Changsha’s five urban districts through a dual-dimensional framework bridging physical (social, economic, cultural, and ecological) and virtual (video, social, and digital life) dimensions. Integrating Coupling Coordination Degree (CCD) and XGBoost-SHAP models, we elucidate the spatial patterns and nonlinear drivers of Virtual-Physical synergy. The results indicate that: (1) Urban Vitality exhibits a significant center-periphery gradient. Although the Coupling Degree between the two dimensions is high, the overall CCD remains relatively low, reflecting pervasive spatial mismatches. Notably, 55 units display a reverse pattern where Virtual Vitality surpasses Physical Vitality, suggesting that digital flows can reconfigure urban space by transcending traditional locational constraints. (2) Interactions within the built environment exert pronounced threshold effects. Structural elements require specific critical masses to activate synergy, beyond which marginal returns diminish, as exemplified by the U-shaped effect of the Green View Index and the inverted U-shaped effect of Spatial Enclosure on CCD. (3) Interaction analysis identifies building density as a multiplier, unlocking the synergistic potential of land-use mix and transport networks once critical thresholds are surpassed. Furthermore, the efficacy of population and transit relies on dense road networks and intersection, while functional diversity buffers against negative micro-environmental impacts. This study advocates for a shift from facility-increment to threshold-triggered precision strategies in urban regeneration, providing empirical support for human-centric planning in the digital twin era. Full article

The 2024 World Heritage inscription of the Beijing Central Axis shifts the focus of historic district governance to quality-oriented urban regeneration. However, evaluating the precise alignment between infrastructural topology and cultural meaning remains a methodological challenge. To move beyond macro-level assumptions, this study constructs a novel “spatial–semantic coupling” diagnostic framework. Integrating multi-source street-view data, Space Syntax, and the zero-shot semantic extraction capabilities of the CLIP model, we performed high-resolution visual semantic identification across 550 fine-grained sampling points in the 6.6 km² South Central Axis Core Area. Rather than merely observing a general “decoupling,” our diagnostic tool successfully mapped the complex spectrum of spatial alignments. While it accurately diagnosed areas with “idle spatial potential”—where high Global Integration (Mean = 0.924) fails to translate into Visual Attraction (r = −0.03) or Historical Perception (r = 0.01)—it also precisely identified “Synergistic” heritage cores and “hidden gems” within capillary hutongs. Furthermore, the framework diagnosed a severe “green island” effect (Mean = 0.26) and a structural contradiction between Spaciousness and Historical Perception (r = −0.33). By utilizing Bivariate LISA to geographically pinpoint these varying coupling characteristics (e.g., severe “High–Low” spatial frictions at gateway transportation hubs), this study establishes a highly scalable, data-driven analytical paradigm for targeted micro-renewal, ensuring the precise alignment of physical centrality and cultural perception in complex historic districts globally. Full article

In the era of urban stock development, the regeneration of historic districts must abandon the misguided approach of large-scale, sweeping transformations and shift toward a micro-regeneration model characterized by small-scale, precise, and incremental interventions. However, as urban renewal enters this stock-based phase, the issues of “physical dissonance” and “cultural discontinuity” in the heritage landscapes of historic districts are becoming increasingly pronounced. To solve this problem, this paper aims to identify the heritage landscape genes of historical districts, explore the characteristics of historical districts, provide operational targets for the micro-renewal of historical districts, guide the implementation of micro-regeneration policies of historical districts, and then improve the quality of historical district heritage landscapes. Taking the Chinese Baroque Block in Harbin as an example, this paper proposes a genetic recognition method for the heritage landscape of historical districts based on the spatial translation of historical information, spatial topology analysis, an improved U-Net deep learning model, and text mining theme analysis. The micro-regeneration path of historical blocks of “gene identification-feature mining-targeted operation-quality improvement” is proposed. The micro-regeneration countermeasures of “gene replacement and texture repair in open space, gene repair and targeted acupuncture in street and alley, gene embedding and catalyst adjustment in courtyard layout, gene recombination and embroidery treatment of architectural style, and retrospective and contextual narrative of intangible genes” are formulated. The heritage landscape gene of historical districts is conducive to the refined control of the characteristics and quality of historical districts and provides new ideas for the micro-regeneration of historical districts in the stock era. Full article

Historical and cultural districts are the outcome of cultural sedimentation brought about by urban development, and they embody distinctive urban historical and cultural connotations. Ignoring the protection of the historical and cultural value contained in streetscapes will not only decrease the life quality of residents but will also diminish distinctive local urban features. This study focused on the Fangcheng historical and cultural district in Shenyang. The scenic beauty estimation method was employed to evaluate urban style and features’ visual quality, while the semantic differential method was used to obtain the subjective perceptual features of samples. The study also systematically explored the dynamic relationship between urban style and features’ quality and subjective perception in historical and cultural districts. The results show that color richness, coherence, iconic status, and continuum all exert significant positive predictive effects on visual preferences regarding urban style and features. Color richness was the primary determinant of urban style and features’ visual quality. Continuum interfaces, a unified spatial texture, and coordinated dimensions contributed significantly to improving urban style and features’ visual quality in historic and cultural districts. The distinctiveness and cultural iconic status of historical and cultural districts enhanced the residents’ identity and place memory. Moreover, the coherence and continuum of style between the old and new elements promoted an integrated aesthetic experience. The evaluation results revealed that the overall visual quality of urban style and features of most streets was medium. However, streets with a higher visual quality cluster among historical streets and commercial streets. The residential streets demonstrated a significantly lower visual quality. Establishing a comprehensive evaluation system that integrates urban style and features, subjective perception, and the style of historical and cultural districts can contribute to covering the shortage in the traditional urban style and features’ research and also provide a basis for urban regeneration at the micro scale. Full article

Street seating serves as a critical medium for stimulating spatial vitality and holds substantial design value in the refined planning of commercial upgrading and quality enhancement in aging districts. As urban regeneration and the optimization of existing built environments have become dominant paradigms in global urban development, the improvement of street quality—given its role as the primary setting for everyday public life—has increasingly depended on the fine-grained design and precise regulation of micro-scale environmental elements. This study takes Pingdeng Street in Zhengzhou, China, and its 33 seating installations as an empirical case. A multi-level analytical framework—comprising the seating ontology level, the seating space level, and the street environment level—was developed to quantitatively examine the relationships between multi-level spatial elements and street vitality intensity. Through correlation and regression analyses, the study systematically investigated the mechanisms by which seating-related elements at different levels influence street vitality. The results indicate that the Green View Index (GVI) is the core driver of street vitality, with the most significant enhancement observed when GVI ranges between 28% and 35%. The synergistic coupling of multi-level seating elements is essential for maximizing street vitality, while optimization pathways vary across different functional seating types. In design practice, high-comfort seating with backrests is recommended, with seating continuity controlled within 0.63–0.90. Seating spaces should adopt moderately enclosed spatial forms, such as eave-covered areas, and be supplemented with adequate lighting facilities. At the street environment level, a GVI of 28–35% and spatial openness of 9–18% should be maintained. The multi-level analytical framework and quantified indicator thresholds established in this study offer a new perspective on the mechanisms linking seating and street vitality. The findings provide a scientific theoretical basis and offer context-sensitive design guidance for the refined renewal of aging urban districts under comparable conditions. Full article

Mitigating heat stress in high-density historical districts remains a critical challenge in urban renewal due to complex morphological heterogeneity. Existing research often relies on isolated intervention measures, lacking systematic, multi-strategy assessments driven by high-precision spatial data. This study addresses this gap by establishing a quantitative framework that couples thermal infrared remote sensing with Computational Fluid Dynamics (CFD) to optimize microclimate responses in Beijing’s Liulichang Historic District. Remote sensing data were utilized to retrieve high-resolution Land Surface Temperature (LST), providing accurate thermal boundary conditions for micro-scale wind-thermal simulations. A baseline scenario (S0) and seven renewal strategies (S1–S7)—integrating varying configurations of greenery, water bodies, and permeable pavements—were evaluated using pedestrian-level comfort indices. Results reveal that single-factor interventions yield marginal improvements or thermodynamic trade-offs; specifically, adding greenery (S1) in narrow street canyons increased aerodynamic roughness, thereby obstructing ventilation and inducing localized warming. Conversely, composite strategies significantly enhanced microclimatic quality. The “greenery-water-permeable pavement” strategy (S4) achieved optimal synergistic effects, characterized by substantial cooling and spatial homogenization. Regression analysis identified water bodies as the dominant cooling driver, where a 10% increase in water coverage resulted in a temperature reduction of approximately 5.17 °C. Conversely, greenery alone showed no statistically significant cooling contribution (p > 0.05) without the synergistic presence of water or pavement modifications. This research suggests that urban renewal in high-temperature zones (>36 °C) should prioritize composite cooling networks. Furthermore, vegetation layouts near wind corridors must be precisely regulated to prevent ventilation degradation. These findings provide a scientific basis for the climate-adaptive sustainable regeneration of culturally significant, high-density urban blocks. Full article

Micro-scale waterfront spaces play a critical role in contemporary urban regeneration by supporting everyday activities and place-based experiences. However, existing studies often rely on linear evaluation approaches and insufficiently address the asymmetric effects of functional, environmental, and cultural attributes on residents’ landscape satisfaction. This study investigates the satisfaction structure of micro-scale waterfront spaces along the Grand Canal in Wuxi, China, with a particular focus on nonlinear demand mechanisms. A mixed-method framework integrating grounded theory, the Delphi method, and the Kano model was employed to identify key landscape attributes and classify their satisfaction effects. The results reveal a hierarchical satisfaction mechanism characterized by “basic–performance–attractive” attributes. Fundamental functional and environmental factors, such as accessibility, safety, water quality, and cultural authenticity, function as must-be attributes that primarily prevent dissatisfaction. Environmental comfort and social facilities act as one-dimensional attributes that linearly enhance satisfaction, while cultural narratives, memory-related elements, and ecological esthetics emerge as attractive attributes that significantly elevate emotional engagement when present. Sensitivity analysis further identifies priority intervention factors with the greatest impact on satisfaction improvement. These findings demonstrate the asymmetric nature of residents’ landscape satisfaction and provide a phased optimization framework for the sustainable regeneration of heritage-based micro-scale waterfront spaces, emphasizing basic reliability, experiential enhancement, and cultural resonance. Full article

Urban public spaces are an essential component of everyday life in urban communities, and micro public spaces have become an important vehicle for improving living environment quality and enhancing ecological benefits in community renewal within built-up areas. From an economic perspective, this study focuses on the quantification of carbon value generated through the renewal of micro public spaces. Four micro public spaces of comparable size but differing locational and functional characteristics, completed in Wuhan in 2023, were selected as case studies. Plant carbon sequestration was estimated using the biomass expansion factor method combined with field-based forestry surveys, while indirect emission reduction associated with residents’ outdoor activities was assessed through spatiotemporal observations of user behavior. These results were further translated into carbon value based on China’s carbon trading standards to support comparative analysis and design-oriented recommendations. The results indicate that direct sequestration significantly outweighs indirect reduction: the carbon storage density of trees ranges from 0.40 to 1.97 kg/m², with the total storage of HRP reaching 11,587.36 kg; in contrast, annual indirect reduction from resident activities is only 1.34–141.19 kg. Carbon sequestration performance is strongly influenced by the presence of large trees, while micro public spaces located in newly developed and commercial areas exhibit substantially lower emission reduction efficiency than those in older and densely populated residential neighborhoods. In addition, the functional attributes of micro public spaces shape age-specific use patterns, thereby significantly affecting emission reduction outcomes. Based on these findings, targeted optimization strategies for micro public space renewal are proposed to support people-oriented, sustainable, and systematic low-carbon urban regeneration. Full article

Green Infrastructure (GI) is crucial for urban climate adaptation, providing ecosystem services like mitigating the urban heat island effect and enhancing stormwater management, alongside benefits for public health and biodiversity. Effective GI implementation remains challenging, particularly in dense, rapidly urbanized mid-Adriatic coastal cities, classified as climate hotspots like other Mediterranean contexts. This paper presents a replicable applied trans-scalar methodology for detailed GI design scenarios, developed through the EU-funded LIFE+ A_GreeNet project to bridge the theory–practice gap and enable pilot implementations in multiple Italian mid-Adriatic coastal municipalities. The research details a comprehensive, multi-disciplinary, five-phase process applied to the Sant’Antonio district of San Benedetto del Tronto—a dense, trafficked urban area projected to face “extremely strong heat stress” by 2050. Design interventions included spatial optimization, strategic species replacement, the creation of vegetated bioretention basins, and systematic pavement de-sealing. The application of the model demonstrated significant improvements: a substantial increase in permeable surface area (+194%), a measurable reduction in the UTCI index (average ENVI-MET simulated reduction of 1.17 °C by 2030), and a series of benefits resulting from increased green space and enhanced meteorological water management. This research offers local authorities a tangible model to accelerate climate-adaptive solutions, showing how precise GI design creates resilient, comfortable, and human-centered urban spaces. Full article

Understanding how the built environment shapes residents’ emotional perceptions in old residential communities (ORCs) is essential for enhancing livability and supporting people-oriented urban regeneration. This study proposes an explainable analytical framework that integrates community attributes, streetscape indicators, and subjective evaluations. Using random forest (RF) regression combined with Shapley Additive Explanations (SHAP), we conducted an empirical study on ten ORCs in Yangzhou, China. A total of 1240 street view images (SVIs) were processed to extract social attributes, including building age, building scale, and point-of-interest (POI) diversity, as well as visual indicators such as walkability, green view index (GVI), and colorfulness. Six emotional perception scores were obtained from the MIT Place Pulse 2.0 model and further calibrated through questionnaires. The results show that the proposed framework effectively captures the spatial determinants of residents’ perceptions, with the model predictions being highly consistent with survey evaluations. Specifically, GVI and street enclosure are positively associated with perceptions of beauty, safety, and vitality, while building aging and functional monotony intensify negative feelings such as oppression and boredom. Visual diversity (VD) enhances aesthetic and vitality perceptions, whereas facility visual entropy demonstrates a dual role—reinforcing safety but potentially inducing oppressive feelings. By integrating interpretable machine learning with geospatial analysis, this study provides both theoretical and practical insights for micro-scale community renewal, and the framework can be extended to multimodal analyses including soundscapes and behavioral pathways. Full article